Models for: Reflectance spectroscopy allows rapid, accurate, and non-destructive estimates of functional traits from pressed leaves

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Persistent link to this item

https://doi.org/10.13020/ycga-7e47
https://hdl.handle.net/11299/228067

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Keywords

pressed leaves

reflectance spectroscopy

PLSR model coefficients

herbarium specimens

Collection period

2017
2020

Date completed

June 20, 2022

Date updated

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Source information

Journal Title

Journal ISSN

Volume Title

Title

Models for: Reflectance spectroscopy allows rapid, accurate, and non-destructive estimates of functional traits from pressed leaves

Published Date

2022-06-23

Authors

Kothari, Shan

Beauchamp-Rioux, Rosalie

Laliberté, Etienne

Cavender-Bares, Jeannine

Group

ASCEND BII, Canadian Airborne Biodiversity Observatory

Author Contact

Cavender-Bares, Jeannine
cavender@umn.edu

Type

Dataset
Statistical Computing Software Code

Abstract

More than ever, ecologists seek to employ herbarium collections to estimate plant functional traits from the past and across biomes. However, many trait measurements are destructive, which may preclude their use on valuable specimens. Researchers increasingly use reflectance spectroscopy to estimate traits from fresh or ground leaves, and to delimit or identify taxa. Here, we extend this body of work to non-destructive measurements on pressed, intact leaves, like those in herbarium collections. Using 618 samples from 68 species, we used partial least-squares regression to build models linking pressed-leaf reflectance spectra to a broad suite of traits, including leaf mass per area (LMA), leaf dry matter content (LDMC), equivalent water thickness, carbon fractions, pigments, and twelve elements. We compared these models to those trained on fresh- or ground-leaf spectra of the same samples. Here, we present the model coefficients and a README that provides examples of how to apply them to other data.

Description

This submission contains the partial least-squares regression (PLSR) model coefficients to accompany the paper “Reflectance spectroscopy allows rapid, accurate, and non-destructive estimates of functional traits from pressed leaves” by Kothari et al. (2022) Methods in Ecology & Evolution. Each set of models for a given trait comprises a .csv file containing 100 models (rows) × wavelengths. The 100 models are derived from a jackknife analysis as described in the paper. To generate trait estimates using a model set, you apply them to the data (see below) and can take the mean or the full distribution of estimates.

Referenced by

Reflectance spectroscopy allows rapid, accurate, and non-destructive estimates of functional traits from pressed leaves Shan Kothari, Rosalie Beauchamp-Rioux, Etienne Laliberté, Jeannine Cavender-Bares bioRxiv 2021
https://doi.org/10.1101/2021.04.21.440856
Reflectance spectroscopy allows rapid, accurate, and non-destructive estimates of functional traits from pressed leaves” Kothari et al. (2022) Methods in Ecology & Evolution

Related to

Shan Kothari. (2022). ShanKothari/pressed-leaf-models: Trait estimation models from fresh-, pressed-, and ground-leaf spectra (v0.0.1). Zenodo.
https://doi.org/10.5281/zenodo.6824407

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License

Attribution 4.0 International (CC BY 4.0)
https://creativecommons.org/licenses/by/4.0/

Publisher

Collections

Data Repository for U of M (DRUM)

Funding information

ASCEND NSF DBI: 2021898
CABO NSERC: 509190-2017

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Previously Published Citation

Suggested citation

Kothari, Shan; Beauchamp-Rioux, Rosalie; Laliberté, Etienne; Cavender-Bares, Jeannine. (2022). Models for: Reflectance spectroscopy allows rapid, accurate, and non-destructive estimates of functional traits from pressed leaves. Retrieved from the Data Repository for the University of Minnesota (DRUM), https://doi.org/10.13020/ycga-7e47.

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